Machine learning survival prediction in esophageal cancer using radiomics and body composition from pretreatment and follow-up T12-level computed tomography

Figure 4 Nomogram: Estimating overall survival for 1-year to 3-year by using feature subset 1, subset 2, subset 3, subset 4 as input data. A: Nomogram: Estimating overall survival (OS) for 1-year to 3-year by using feature subset 1 as input data; B: Nomogram: Estimating OS for 1-year to 3-year by using feature subset 2 as input data; C: Nomogram: Estimating OS for 1-year to 3-year by using feature subset 3 as input data; D: Nomogram: Estimating OS for 1-year to 3-year by using feature subset 4 as input data. ECOG: Eastern Cooperative Oncology Group; TATSMR1: Total adipose tissue index/skeletal muscle index ratio; sarco: Sarcopenia; 0: Pretreatment; VAT: Visceral adipose tissue; 1: Follow-up; glcm: Gray-level co-occurrence matrix; SAT: Subcutaneous adipose tissue; glszm: Gray-level size zone matrix; glrlm: Gray-level run length matrix; gldm: Gray-level dependence matrix.